Evaluation of Different Internal Structure and Build Orientation for Multijet Modeling Process
Bibliographic record
Abstract
Rapid Prototyping (RP) technology has proven its capability to produce complex parts with shorter lead time. This advantage could benefit tremendously in application such as the Investment Casting (IC) process. The focus of the study is the production of sacrificial IC patterns produced using Multijet Modeling (MJM) RP technology. It includes the evaluation of dimensional accuracy and the surface roughness of part with a hollow and quasi hollow inner support patterns. Different internal structure's pattern were developed using CAD software, and the part were fabricated using MJM technique in two different build orientations. Analyses were done using Coordinate Measuring Machine (CMM) and the surface roughness tester. Results show that part built with 90º orientation is better than part built with 0º orientation both in terms of accuracies and roughness. Different internal structure similarly affects the final part quality, though the post processing steps also have their influence, thus making it no clear different among the parts. However, it demonstrated parts with square structure produced the best dimensional accuracy and the part with hatch structure produced the best surface roughness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".